NFL Week 6, 2018 Season

Purely from a personal fan perspective, a better week than others. Both of the teams I follow won this weekend. Atlanta squeaked by Tampa Bay, and Dallas demolished Jacksonville. Why Jacksonville single covered Cole Beasley is anyone’s guess.

Kansas City fell from the ranks of the unbeaten and Baltimore, with a terrific defensive performance, kept its high ranking at the top of the SRS charts.

Just as a reminder, SRS as calculated by this code corresponds exactly to the old version used by Pro Football Reference. You can test this by using the Wayback Machine to say, 2012 and comparing results.

Looking at ESPN’s QBR stat, do you get the impression it is heavily influenced by a couple huge games? Ryan Fitzpatrick is still the fifth ranked quarterback in the whole league.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
93         59     63.4      28.73        18.46     10.27

Calculated Pythagorean Exponent:  2.69


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     LA       9.5     6   6   0   0 100.0  79.7  11.27  13.00 -1.73
2     KC       7.5     6   5   1   0  83.3  64.6   8.12   7.17  0.95
3     NO       6.0     5   4   1   0  80.0  66.3   5.09   8.00 -2.91
4     BAL     12.5     6   4   2   0  66.7  86.4  11.87  12.67 -0.79
5     LAC      6.5     6   4   2   0  66.7  62.8   4.43   5.17 -0.73
6     CIN      5.5     6   4   2   0  66.7  56.5   4.41   2.67  1.74
7     NE       5.0     6   4   2   0  66.7  61.4   3.73   4.67 -0.94
8     MIA      5.0     6   4   2   0  66.7  42.7  -1.67  -2.50  0.83
9     WAS      6.0     5   3   2   0  60.0  51.3  -1.17   0.40 -1.57
10    CHI      2.0     5   3   2   0  60.0  73.0   6.65   8.60 -1.95
11    CAR      2.0     5   3   2   0  60.0  54.0   0.44   1.40 -0.96
12    PIT      1.5     6   3   2   1  58.3  57.0   5.91   2.83  3.08
13    MIN      1.0     6   3   2   1  58.3  46.3  -3.79  -1.33 -2.46
14    GB       0.5     6   3   2   1  58.3  51.8  -2.05   0.67 -2.72
15    NYJ      2.0     6   3   3   0  50.0  61.3   2.54   4.33 -1.79
16    PHI      1.0     6   3   3   0  50.0  60.5  -0.87   3.33 -4.20
17    JAX      1.0     6   3   3   0  50.0  40.4  -2.14  -2.83  0.69
18    TEN      1.0     6   3   3   0  50.0  36.4  -4.41  -3.33 -1.08
19    SEA      0.5     6   3   3   0  50.0  63.2   4.93   4.33  0.59
20    HOU      0.0     6   3   3   0  50.0  49.0  -3.71  -0.33 -3.38
21    DAL     -0.5     6   3   3   0  50.0  61.7   1.62   3.33 -1.71
22    CLE     -1.5     6   2   3   1  41.7  39.1  -0.18  -3.83  3.65
23    DET     -2.0     5   2   3   0  40.0  43.9  -2.37  -2.40  0.03
24    TB      -3.0     5   2   3   0  40.0  36.6  -3.49  -6.40  2.91
25    ATL     -3.5     6   2   4   0  33.3  40.7  -2.25  -4.17  1.91
26    DEN     -3.5     6   2   4   0  33.3  33.8  -0.54  -5.67  5.13
27    BUF     -9.0     6   2   4   0  33.3  16.7  -9.94 -10.33  0.39
28    SF      -5.5     6   1   5   0  16.7  37.5  -5.69  -5.17 -0.52
29    IND     -6.0     6   1   5   0  16.7  38.8  -3.85  -4.67  0.82
30    NYG     -6.0     6   1   5   0  16.7  29.4  -7.43  -7.50  0.07
31    ARI     -6.5     6   1   5   0  16.7  19.5  -7.47  -9.50  2.03
32    OAK    -12.0     6   1   5   0  16.7  22.0  -7.96 -11.00  3.04

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NFL Week 5, 2018 season

In the chase for teams that might approach the 1950 Los Angeles Rams as the highest scoring team in history, the Saints are now scoring at a pace of 36.0 points a game. The LA Rams and Kansas City Chiefs are just a few points behind. That said, it’s an odd season. The Falcons are 1-4, the whole NFC East is in a bad way, and it’s reasonable to ask if John Gruden trading Khalil Mack didn’t flip everything for the Chicago Bears.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
78         50     64.1      28.31        18.35      9.96

Calculated Pythagorean Exponent:  2.96


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     LA      12.0     5   5   0   0 100.0  84.4  11.84  15.00 -3.16
2     KC      10.0     5   5   0   0 100.0  71.2   9.91   9.20  0.71
3     CIN     10.0     5   4   1   0  80.0  61.8   5.13   4.60  0.53
4     NO       6.0     5   4   1   0  80.0  67.8   6.51   8.00 -1.49
5     CAR      5.0     4   3   1   0  75.0  59.8   1.76   3.25 -1.49
6     CHI      4.5     4   3   1   0  75.0  83.0   9.02  11.50 -2.48
7     BAL     12.0     5   3   2   0  60.0  83.2  11.62  11.00  0.62
8     NE       7.0     5   3   2   0  60.0  65.0   2.77   5.00 -2.23
9     MIA      7.0     5   3   2   0  60.0  37.9  -3.11  -3.60  0.49
10    JAX      5.0     5   3   2   0  60.0  62.4   5.05   3.20  1.85
11    TEN      3.0     5   3   2   0  60.0  50.9  -3.31   0.20 -3.51
12    LAC      2.0     5   3   2   0  60.0  53.9   1.03   1.40 -0.37
13    TB       1.5     4   2   2   0  50.0  34.5  -2.34  -6.75  4.41
14    WAS      1.0     4   2   2   0  50.0  46.5  -2.94  -1.00 -1.94
15    PIT      0.0     5   2   2   1  50.0  55.4   6.18   2.00  4.18
16    GB       0.0     5   2   2   1  50.0  50.6  -2.77   0.20 -2.97
17    CLE      0.0     5   2   2   1  50.0  50.7   4.63   0.20  4.43
18    MIN      0.0     5   2   2   1  50.0  39.2  -6.14  -3.60 -2.54
19    DET     -2.0     5   2   3   0  40.0  43.2  -3.86  -2.40 -1.46
20    SEA     -2.0     5   2   3   0  40.0  51.3   1.97   0.40  1.57
21    PHI     -2.0     5   2   3   0  40.0  49.3  -4.08  -0.20 -3.88
22    HOU     -3.0     5   2   3   0  40.0  44.4  -4.49  -1.80 -2.69
23    DAL     -3.0     5   2   3   0  40.0  39.4  -4.31  -2.60 -1.71
24    NYJ     -4.0     5   2   3   0  40.0  61.5   3.75   3.60  0.15
25    DEN     -4.0     5   2   3   0  40.0  31.0  -1.93  -6.20  4.27
26    BUF    -11.0     5   2   3   0  40.0  13.5 -10.91 -11.00  0.09
27    ARI     -3.0     5   1   4   0  20.0  16.6  -6.78  -9.40  2.62
28    IND     -4.0     5   1   4   0  20.0  38.6  -4.72  -4.00 -0.72
29    NYG     -5.0     5   1   4   0  20.0  35.1  -3.90  -4.80  0.90
30    ATL     -6.0     5   1   4   0  20.0  35.4  -2.90  -6.00  3.10
31    SF      -8.0     5   1   4   0  20.0  34.7  -6.77  -5.60 -1.17
32    OAK     -8.0     5   1   4   0  20.0  27.3  -5.91  -8.40  2.49

 

NFL Week 4, 2018 season

Somewhere around the third or fourth game the Simple Ranking System begius to resolve, and it did resolve on the third week, but the results were weird. What to think of New England as the 29th team in the NFL? Not as much. Even the fourth week will have its oddities, as it considers the Baltimore Ravens as the best team in the league, probably off the massive win in week 1. The other early story line is whether or not this is a historic season for scoring. Last I checked, the 1950 Las Angelas Rams held the scoring lead for a season at 38.8 points a game, and the 2018 Rams are clipping along at a mere 35 points a game. Not quite there yet.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
63         38     60.3      28.21        18.30      9.90

Calculated Pythagorean Exponent:  3.16


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     LA      16.0     4   4   0   0 100.0  91.2  12.78  18.25 -5.47
2     KC       7.5     4   4   0   0 100.0  67.6   4.77   7.50 -2.73
3     BAL     12.5     4   3   1   0  75.0  88.3  13.59  14.50 -0.91
4     JAX      8.0     4   3   1   0  75.0  80.7   6.43   8.00 -1.57
5     MIA      7.5     4   3   1   0  75.0  42.7  -3.32  -2.00 -1.32
6     CIN      6.0     4   3   1   0  75.0  58.5   9.26   3.25  6.01
7     NO       4.5     4   3   1   0  75.0  59.7   1.97   4.00 -2.03
8     CHI      4.5     4   3   1   0  75.0  84.5   8.87  11.50 -2.63
9     TEN      3.0     4   3   1   0  75.0  52.1   0.41   0.50 -0.09
10    WAS     14.0     3   2   1   0  66.7  76.6   4.77   6.67 -1.89
11    CAR      8.0     3   2   1   0  66.7  63.0   6.32   3.67  2.65
12    GB       0.5     4   2   1   1  62.5  58.1   0.74   2.25 -1.51
13    TB       1.5     4   2   2   0  50.0  33.5  -4.03  -6.75  2.72
14    PHI      0.5     4   2   2   0  50.0  51.0   0.37   0.25  0.12
15    SEA      0.0     4   2   2   0  50.0  53.8   0.34   1.00 -0.66
16    DEN     -1.5     4   2   2   0  50.0  38.8   0.31  -3.25  3.56
17    NE      -2.0     4   2   2   0  50.0  59.6   0.48   2.75 -2.27
18    DAL     -3.0     4   2   2   0  50.0  39.2  -4.28  -2.50 -1.78
19    LAC     -4.0     4   2   2   0  50.0  43.9  -3.04  -2.25 -0.79
20    CLE     -1.5     4   1   2   1  37.5  48.5  -1.63  -0.50 -1.13
21    PIT     -2.5     4   1   2   1  37.5  40.0  -0.32  -3.50  3.18
22    MIN     -3.5     4   1   2   1  37.5  34.6  -6.80  -5.00 -1.80
23    DET     -2.5     4   1   3   0  25.0  35.2  -8.34  -5.00 -3.34
24    ATL     -3.5     4   1   3   0  25.0  46.0   2.98  -1.50  4.48
25    IND     -3.5     4   1   3   0  25.0  45.1   1.14  -1.50  2.64
26    HOU     -4.0     4   1   3   0  25.0  40.8  -3.85  -3.00 -0.85
27    OAK     -4.5     4   1   3   0  25.0  32.0  -4.47  -6.50  2.03
28    SF      -5.0     4   1   3   0  25.0  37.2  -7.85  -4.50 -3.35
29    NYJ     -6.0     4   1   3   0  25.0  50.0  -1.72   0.00 -1.72
30    NYG     -6.0     4   1   3   0  25.0  30.3  -5.43  -5.50  0.07
31    BUF    -16.5     4   1   3   0  25.0   8.5 -12.88 -14.00  1.12
32    ARI    -10.5     4   0   4   0   0.0   5.0  -7.56 -14.25  6.69

 

Trades on day 1 of the 2018 Draft. AV analysis.

Bill traded up to pick 7 to get QB Josh Allen.

Josh Allen Trade
Buffalo Bills		Buccaneers		Results
Pick	Average AV	Pick	Average AV	Delta AV	Risk Ratio
7	32	12	35
		53	22
		56	19
Total	32	Total	76
				44	2.38

~~~
The Cards moved up to pick 10 to draft Josh Rosen
~~~

Josh Rosen Trade
Cardinals		Raiders		Results
Pick	Average AV	Pick	Average AV	Delta AV	Risk Ratio
10	41	15	28
		79	18
		152	9
Total	41	Total	55
				14	1.34

~~~
Saints move up to get Marcus Davenport, DE
~~~

Marcus Davenport Trade
Saints		Packers		Results
Pick	Average AV	Pick	Average AV	Delta AV	Risk Ratio
14	29	27	25
		147	8
		(25)	24
Total	29	Total	57
				28	1.97

~~~
Bills go up to get Tremaine Edmunds
~~~

Tremaine Edmunds Trade
Bills		Ravens		Results
Pick	Average AV	Pick	Average AV	Delta AV	Risk Ratio
16	32	22	27
154	12	65	21
Total	44	Total	48
				4	1.09

~~~
Packers trade again to get Jaire Alexander
~~~

Jaire Alexander Trade
Packers		Seahawks		Results
Pick	Average AV	Pick	Average AV	Delta AV	Risk Ratio
18	29	27	25
248	5	76	17
		188	5
Total	34	Total	47
				13	1.38

~~~
Titans trade up for Rashaan Evans
~~~

Jaire Alexander Trade
Packers		Seahawks		Results
Pick	Average AV	Pick	Average AV	Delta AV	Risk Ratio
18	29	27	25
248	5	76	17
		188	5
Total	34	Total	47
				13	1.38

~~~
Ravens trade 2019 assets to get their QB
~~~

Lamar Jackson Trade
Ravens		Eagles		Results
Pick	Average AV	Pick	Average AV	Delta AV	Risk Ratio
32	23	52	22
132	11	125	15
		(48)	25
Total	34	Total	62
				28	1.82

 

My computer draft simulator revisited (with a mock draft).

The first version of my Open Source Draft Simulator I wrote in time to analyze the draft of 2001, and it was based on C++. Later on, in 2007, while trying to get a job, I rewrote the simulator in Ruby because I was trying to impress people that I could learn the language. I didn’t get the job. The Ruby simulator isn’t as statistically versatile, but it works on multiple sports.

I pulled out that ten year old code, in part to see if it still works, and part to see if I could make use of the data I had received from Ourlads. Ourlads does a 32 team needs list, which in general is the hardest part of setting up a draft simulator.

The ruby code, as downloaded, has a dependence on the module ‘rdoc/usage’. It is not essential, and I recommend you comment out or delete the line that says ‘require ‘rdoc/usage”. At that point you’ll have a working program. If all the warnings at the beginning bother you, remove the -w flag from the hash bang (first) line.

On Linux create all the files and then get rid of the ^Ms at the end of the lines. I had originally developed this sim on Windows. You can use perl to remove the ^M characters with something like perl -pre ‘s/\r//g’.

Data sources? Sports Illustrated has a top 100 list that works well. The top 100 list from NFL Draft Scout also yields useful results. I used Ourlads as my ‘serious’ set of needs, but Lance Zierlein has a set, as do other sites.

A typical rule file in my current setup is:

#
# rule file for Cleveland Browns.
#
rule need
#
needlist QB RB OL DB DE
#
cond QB max 1 high 
#
cond RB max 1

To note, with the SI top player set, if you don’t set QB to a “high” need, you’ll end up drafting Saquon Barkley number one. That’s one of the things I like about my own code. Slight changes in the needs of a single team can cause ripple effects throughout the draft.

A typical mock draft using this setup is:

ruby rubysim.rb -y 2018 -s football

This mock draft was made by rubysim.rb on 2018-04-16


Round 1.

1. Cleveland Browns select Sam Darnold, QB.
2. New York Giants select Bradley Chubb, DE.
3. New York Jets select Baker Mayfield, QB.
4. Cleveland Browns select Saquon Barkley, RB.
5. Denver Broncos select Josh Allen, QB.
6. Indianapolis Colts select Quenton Nelson, G.
7. Tampa Bay Buccaneers select Minkah Fitzpatrick, S.
8. Chicago Bears select Roquan Smith, LB.
9. San Francisco 49ers select Calvin Ridley, WR.
10. Oakland Raiders select Denzel Ward, CB.
11. Miami Dolphins select Vita Vea, DT.
12. Buffalo Bills select Josh Rosen, QB.
13. Washington Redskins select Josh Jackson, CB.
14. Green Bay Packers select Derwin James, S.
15. Arizona Cardinals select Connor Williams, OT.
16. Baltimore Ravens select Mike McGlinchey, OT.
17. Los Angeles Chargers select Tremaine Edmunds, LB.
18. Seattle Seahawks select Marcus Davenport, DE.
19. Dallas Cowboys select Da'Ron Payne, DT.
20. Detroit Lions select Harold Landry, DE.
21. Cincinnati Bengals select Leighton Vander Esch, LB.
22. Buffalo Bills select Courtland Sutton, WR.
23. New England Patriots select Derrius Guice, RB.
24. Carolina Panthers select Isaiah Oliver, CB.
25. Tennessee Titans select Maurice Hurst, DT.
26. Atlanta Falcons select Taven Bryan, DL.
27. New Orleans Saints select Christian Kirk, WR.
28. Pittsburgh Steelers select Rashaan Evans, LB.
29. Jacksonville Jaguars select Kolton Miller, OT.
30. Minnesota Vikings select Arden Key, DE.
31. New England Patriots select Isaiah Wynn, G.
32. Philadelphia Eagles select Justin Reid, S.

Round 2.

33. Cleveland Browns select James Daniels, C.
34. New York Giants select Lamar Jackson, QB.
35. Cleveland Browns select Mike Hughes, CB.
36. Indianapolis Colts select Jaire Alexander, CB.
37. Indianapolis Colts select Ronnie Harrison, S.
38. Tampa Bay Buccaneers select Carlton Davis, CB.
39. Chicago Bears select D.J. Moore, WR.
40. Denver Broncos select Hayden Hurst, TE.
41. Oakland Raiders select Donte Jackson, CB.
42. Miami Dolphins select Ronald Jones II, RB.
43. New England Patriots select Mike Gesicki, TE.
44. Washington Redskins select Will Hernandez, G.
45. Green Bay Packers select Orlando Brown, OT.
46. Cincinnati Bengals select Billy Price, C.
47. Arizona Cardinals select Chukwuma Okorafor, OT.
48. Los Angeles Chargers select Rasheem Green, DT.
49. Indianapolis Colts select Sam Hubbard, DE.
50. Dallas Cowboys select James Washington, WR.
51. Detroit Lions select Brian O'Neill, OT.
52. Baltimore Ravens select Jessie Bates, S.
53. Buffalo Bills select Deon Cain, WR.
54. Kansas City Chiefs select Tim Settle, DT.
55. Carolina Panthers select Lorenzo Carter, DE.
56. Buffalo Bills select Martinas Rankin, OT.
57. Tennessee Titans select Armani Watts, S.
58. Atlanta Falcons select Harrison Phillips, DT.
59. San Francisco 49ers select Uchenna Nwosu, LB.
60. Pittsburgh Steelers select Dallas Goedert, TE.
61. Jacksonville Jaguars select Anthony Averett, CB.
62. Minnesota Vikings select DeShon Elliott, S.
63. New England Patriots select Tyrell Crosby, OT.
64. Cleveland Browns select Ogbonnia Okoronkwo, DE.

Round 3.

65. Buffalo Bills select Darius Leonard, LB.
66. New York Giants select Sony Michel, RB.
67. Indianapolis Colts select Desmond Harrison, OT.
68. Houston Texans select Mark Andrews, TE.
69. New York Giants select Mason Rudolph, QB.
70. San Francisco 49ers select Dante Pettis, WR.
71. Denver Broncos select Kerryon Johnson, RB.
72. New York Jets select Nick Chubb, RB.
73. Miami Dolphins select Jerome Baker, LB.
74. San Francisco 49ers select Equanimeous St. Brown, WR.
75. Oakland Raiders select Malik Jefferson, LB.
76. Green Bay Packers select Michael Gallup, WR.
77. Cincinnati Bengals select Ian Thomas, TE.
78. Washington Redskins select Frank Ragnow, C.
79. Arizona Cardinals select Geron Christian, OT.
80. Houston Texans select Kyzir White, S.
81. Dallas Cowboys select Jamarco Jones, OT.
82. Detroit Lions select Jeff Holland, DE.
83. Baltimore Colts select Josh Sweat, DE.
84. Los Angeles Chargers select Trenton Thompson, DT.
85. Carolina Panthers select D.J. Chark, WR.
86. Kansas City Chiefs select Braden Smith, G.
87. Los Angeles Rams select Kemoko Turay, DE.
88. Carolina Panthers select Dorance Armstrong Jr., DE.
89. Tennessee Titans select Tarvarus McFadden, CB.
90. Atlanta Falcons select Chad Thomas, DE.
91. New Orleans Saints select Jordan Lasley, WR.
92. Pittsburgh Steelers select Shaquem Griffin, OLB.
93. Jacksonville Jaguars select Rashaan Gaulden, CB.
94. Minnesota Vikings select Tre'Quan Smith, WR.
95. New England Patriots select Anthony Miller, WR.
96. Buffalo Bills select Simmie Cobbs Jr., WR.
97. Arizona Cardinals select Joseph Noteboom, OT.
98. Houston Texans select Nick Nelson, CB.
99. Denver Broncos select Rashaad Penny, RB.
100. Cincinnati Bengals select Jaylen Samuels, RB.

 

The Myth of the Tom Landry 4-3 two gap.

I suspect this whole narrative was kick started by an article in Cowboys Nation that invented something they called the even 4-3. That nothing prior to CN ever talked about a Tom Landry even 4-3 did not stop them, nor did books that mentioned that Tom Landry’s first two defenses were the 4-3 inside and the 4-3 outside. Again, you don’t have to believe me. Read Peter Golenbock’s book on the Dallas Cowboys. We’ll start quoting from page 47 (1).

As a player Landry would not have been presumptive enough to try to formally teach his system to the other defensive players, but as defensive coach, it became his job. He designed a defense he called “the inside 4-3” and “the outside 4-3”.

Going to stop. He didn’t call his defense the even 4-3. The names were 4-3 inside and 4-3 outside.

It was revolutionary because everyone in the past everyone played man-to-man defense. In the past brute strength had been the requisite. You lined up opposite your man, and you tried to beat the crap out of him, using a forearm or your shoulder or a headslap or grabbing him by the jersey and throwing him to one side in an attempt to get by him to make the tackle.

Note that a “gladitorial style” has a lot in common with a modern two gap. It’s a head on collision with the man in front of you.

So what were these revolutionary new assignments? Turns out we know because Vince Lombardi took the 43 inside and outside to Green Bay and those defenses he used for the rest of his coaching career. Later, a book called “Vince Lombardi on Football” was written and in that book, every assignment of every player was documented. We’ll borrow some images from my article on the 43 Flex.

To note, the 4 linemen in the 4-3 inside/outside are not flush on the line. The tackles are flexed, or about three feet behind the line.

Assignments for the line are single gaps. In the inside, the tackles take an A gap and the middle linebacker takes the B gaps. In the outside, the tackles take a B gap and the middle linebacker is responsible for the two A gaps.

Vince Lombardi on the 4-3 inside

Vince Lombardi on the 4-3 outside

Ok, so maybe his first defenses were one gap defenses. Perhaps the even 4-3 was a change of pace? Perhaps the Flex was a two gap defense? Again, the evidence suggests otherwise. Golenbock, quoting Dick Nolan (2).

What Tom came up with was the Flex, a combination of the 4-3 inside and the 4-3 outside defenses. On one side you’re playing an inside, and on the other side, you’re playing an outside.

We had been a strictly an inside-outside 4-3 team, like the old Giants, and then in ’64, we used the Flex as a change-up defense…

So, no, Dallas didn’t use a third defense, and neither did the Tom Landry Giants. Those defenses were one gap defenses, and so was the Flex. This can be confirmed by Lee Roy Jordan himself (1).

In a nutshell, here is the best layman way I can describe the Flex. There are eight natural gaps on the front line, and in the 4-3 that most teams were using, the four down linemen were asked to control two gaps each. In essence, Coach Landry created a picket fence look, with our right end and left tackle lined up in the conventional spot on the line but the left end and right tackle lined up a few feet off the line, giving them better pursuit angles. The linemen had to control only one gap. The middle linebacker spot now had to control the two gaps on either side of the center. The defense allowed the defensive backs and linebackers to force the play to go where the running backs didn’t want to go. It sure helped me make a lot of tackles during my career. It was a revolutionary defense and created a lot of the motion and spread offenses you see today.

If the description seems confusing, please note that hard core Tom Landry disciples describe the defense “as a QB might see it”, as opposed to the more conventional “as a MLB might see it”. So, in the description above, Bob Lilly or Randy White would have been the left tackle, whereas in conventional notation, they would be considered right tackles.

43 flex. Left to right, front is “4-2-2-5”.

Just to be sure, I got on Facebook and asked Pat Toomay about the notion that Tom used two gap defenses. He replied. To quote Pat:

In a straight inside or outside 4-3, linemen take outside shoulders while MLB has two gap. Not a good run defense, although slanting one way or another was an option for other teams but not for Landry. Hence the Flex. Outside blow-and-go 4-3 was for obvious passing situations. In 3-4 defenses, everybody up front has 2-gap. You need fire-plug linemen for that one. By comparison, Landry’s guys were tall and quick, who were required to take a shoulder rather than go head up, a battle they were unlikely to win, if that makes sense.

In summary, Tom’s defenses were all one gap defenses, where the middle linebacker covered two gaps. As Pat Toomay astutely points out, his linemen were not built to handle a two gap. They were chosen to penetrate and be disruptive. But as Lee Roy Jordan does point out, other defenses of his era did two gap. So the search for the 43 two gap really should extend to other innovative defenders of the era, which would be the Clark Shaughnessy/George Allen Chicago Bears or perhaps the elite defensive teams of the Detroit Lions. I would suggest looking to those teams using 4-3 over and under defensive fronts, as having a tackle over the center lends itself to such a scheme.

Notes

1. Golenbock, p 47
2. Golenbock, p. 233
3. Jordan and Townsend, chapter 10, “The Summer of 1964”.

Bibliography

Flynn, George L (ed), Vince Lombardi On Football, Wallynn Inc, 1973

Golenbock, Peter, Cowboys Have Always Been My Heroes, Warner Books, 1997

Jordan, Lee Roy and Townsend, Steve, Lee Roy: My Story of Faith, Family, and Football, Wood Publishing, 2017 [ebook]

 

The Jets – Colts trade is one of the riskiest trades in recent history.

There are a number of ways to analyze a draft trade. You can do it by comparing the actual players selected (though that takes time), you can do it by trade value, as measured by a trade chart, or you can do it by using the Pro Football Reference statistic approximate value. There are charts of approximate value per draft choice and those charts can be used to calculate trade values and risk immediately.

The recent blockbuster trade by the Jets involves substantially more risk than the last five major trade ups in the NFL (here, here and here). To make these calculations I assume the Jet’s pick next year will be the 10th pick in the second round, hence the 42nd pick.

Trade for 3rd Pick
Jets		Colts		Results
Pick	Average AV	Pick	Average AV	Delta AV	Risk Ratio
3	45	6	39
		37	28
		49	20
		42	25
Total	45	Total	112
				67	2.49

 

With a risk ratio of 2.7 2,5, the risk incurred by the Jets is a bit less to what Washington put up with in the RGIII trade. It’s also comparable to the Earl Campbell trade. The last two trades were high risk – never paid back kinds of trades (though with Earl Campbell, the team’s competitiveness during his peak years may have been enough emotionally for the Oilers).

Update: recalculated risk, which now stands at 2.5 instead of 2.7.